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This article discusses the opportunities, applications and future directions of large-scale pre-trained models, i.e., foundation models, for analyzing medical images.
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Sihong Chen, Kai Ma, and Yefeng Zheng · 2019
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Internimage: Exploring large-scale vision foundation models with deformable convolutions
Wenhai Wang, Jifeng Dai, Zhe Chen, Zhenhang Huang, Zhiqi Li, Xizhou Zhu, Xiaowei Hu, Tong Lu, Lewei Lu, Hongsheng Li, et al · 2022
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Self-supervised learning from 100 million medical images
Florin C Ghesu, Bogdan Georgescu, Awais Mansoor, Youngjin Yoo, Dominik Neumann, Pragneshkumar Patel, RS Vishwanath, James M Balter, Yue Cao, Sasa Grbic, et al · 2022
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Expert-level detection of pathologies from unannotated chest x-ray images via self-supervised learning
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Scaling vision transformers to gigapixel images via hierarchical self-supervised learning
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The medical segmentation decathlon
Michela Antonelli, Annika Reinke, Spyridon Bakas, Keyvan Farahani, Annette Kopp-Schneider, Bennett A Landman, Geert Litjens, Bjoern Menze, Olaf Ronneberger, Ronald M Summers, et al · 2022
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Self-supervised pre-training of swin transformers for 3d medical image analysis
Yucheng Tang, Dong Yang, Wenqi Li, Holger R Roth, Bennett Landman, Daguang Xu, Vishwesh Nath, and Ali Hatamizadeh · 2022
Segment anything model for medical image analysis: an experimental study
Maciej A Mazurowski, Haoyu Dong, Hanxue Gu, Jichen Yang, Nicholas Konz, and Yixin Zhang · 2023
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Generalist vision foundation models for medical imaging: A case study of segment anything model on zero-shot medical segmentation
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A whole-body fdg-pet/ct dataset with manually annotated tumor lesions
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Isles 2022: A multi-center magnetic resonance imaging stroke lesion segmentation dataset
Moritz R Hernandez Petzsche, Ezequiel de la Rosa, Uta Hanning, Roland Wiest, Waldo Valenzuela, Mauricio Reyes, Maria Meyer, Sook-Lei Liew, Florian Kofler, Ivan Ezhov, et al · 2022
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Digestpath: A benchmark dataset with challenge review for the pathological detection and segmentation of digestive-system
Qian Da, Xiaodi Huang, Zhongyu Li, Yanfei Zuo, Chenbin Zhang, Jingxin Liu, Wen Chen, Jiahui Li, Dou Xu, Zhiqiang Hu, et al · 2022
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Roentgen: vision-language foundation model for chest x-ray generation
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Brain imaging generation with latent diffusion models
Walter HL Pinaya, Petru-Daniel Tudosiu, Jessica Dafflon, Pedro F Da Costa, Virginia Fernandez, Parashkev Nachev, Sebastien Ourselin, and M Jorge Cardoso · 2022
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3dsam-adapter: Holistic adaptation of sam from 2d to 3d for promptable medical image segmentation
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Sam on medical images: A comprehensive study on three prompt modes
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Virchow: A million-slide digital pathology foundation model
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A foundation model for generalizable disease detection from retinal images
Yukun Zhou, Mark A Chia, Siegfried K Wagner, Murat S Ayhan, Dominic J Williamson, Robbert R Struyven, Timing Liu, Moucheng Xu, Mateo G Lozano, Peter Woodward-Court, et al · 2023
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Universeg: Universal medical image segmentation
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Coen De Vente, Koenraad A Vermeer, Nicolas Jaccard, He Wang, Hongyi Sun, Firas Khader, Daniel Truhn, Temirgali Aimyshev, Yerkebulan Zhanibekuly, Tien-Dung Le, et al · 2023
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Totalsegmentator: Robust segmentation of 104 anatomic structures in ct images
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Towards general purpose medical ai: Continual learning medical foundation model
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Unified chest x-ray and radiology report generation model with multi-view chest x-rays
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